Further investigation on time-domain maximum likelihood estimation of chirp signal parameters

• Published in: IET signal processing Vol. 7; no. 5; pp. 444 - 449
• Main Authors: Deng, Zhen-miao, Ye, Lin-mei, Fu, Mao-zhong, Lin, Shi-jun, Zhang, Yi-xiong
• Format: Journal Article
• Language: English
• Published: Stevenage The Institution of Engineering and Technology 01.07.2013; Institution of Engineering and Technology; The Institution of Engineering & Technology
• Subjects: Algorithms; amplitude weighted phase‐based estimators; Amplitudes; Applied sciences; chirp signal parameters; Chirp signals; Cramer–Rao lower bound; differenced‐phase prediction; DPP‐UA; Estimators; Exact sciences and technology; Image processing; Information, signal and communications theory; Lower bounds; Maximum likelihood estimation; optimal number; Optimization; phase‐unwrapping algorithms; Signal processing; Signal to noise ratio; signal‐to‐noise ratio conditions; SNR conditions; Telecommunications and information theory; time‐domain analysis; time‐domain maximum likelihood estimation; DPP-UA; signal processing; phase-unwrapping algorithms; time-domain analysis; amplitude weighted phase-based estimators; differenced-phase prediction; signal-to-noise ratio conditions; maximum likelihood estimation; SNR conditions; time-domain maximum likelihood estimation; chirp signal parameters; optimal number; Cramer–Rao lower bound; Performance evaluation; Phase unwrapping; Time domain method; Image processing; Chirp pulse; Maximum likelihood; Image restoration; Algorithm; Cramer Rao inequality; Signal to noise ratio
• ISSN: 1751-9675; 1751-9683; 1751-9683
• DOI: 10.1049/iet-spr.2011.0422

The time-domain maximum likelihood estimation of chirp signal parameters is investigated in this study. Three amplitude weighted phase-based estimators and two phase-unwrapping algorithms, that is, phase prediction and unwrapping algorithm (PP-UA) and differenced-phase prediction and unwrapping algorithm (DPP-UA) were proposed. The DPP-UA and PP-UA have their merits and drawbacks. The authors combine the merits of these two methods and propose a new phase-unwrapping algorithm, which outperforms PP-UA and DPP-UA under low signal-to-noise ratio (SNR) conditions. The authors’ further study on the optimal number of initial data sample show that it is SNR-related and can be determined according to the ‘3σ’ rule and the Cramer–Rao lower bound.